Tapestry: A Single-Round Smart Pooling Technique for COVID-19 Testing

Abstract

The COVID-19 pandemic has strained testing capabilities worldwide. There is an urgent need to find economical and scalable ways to test more people. We present Tapestry, a novel quantitative nonadaptive pooling scheme to test many samples using only a few tests. The underlying molecular diagnostic test is any real-time RT-PCR diagnostic panel approved for the detection of the SARS-CoV-2 virus. In cases where most samples are negative for the virus, Tapestry accurately identifies the status of each individual sample with a single round of testing in fewer tests than simple two-round pooling. We also present a companion Android application BYOM Smart Testing which guides users through the pipetting steps required to perform the combinatorial pooling. The results of the pooled tests can be fed into the application to recover the status and estimated viral load for each individual sample. NOTE: This protocol has been validated with in vitro experiments that used synthetic RNA and DNA fragments and additionally, its expected behavior has been confirmed using computer simulations. Validation with clinical samples is ongoing. We are looking for clinical collaborators with access to patient samples. Please contact the corresponding author if you wish to validate this protocol on clinical samples.

Pooling of coronavirus tests under unknown prevalence

“…The pooling method was validated for nCov tests by many laboratories [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. However, the following questions remained open, which we address in this paper.…”

Two-Stage Adaptive Pooling with RT-qPCR for COVID-19 Screening

“…Three different values of number of infected people in the population (k), namely k ∈ {5, 10, 15}, have been considered. For every k, we performed 100 Monte-Carlo simulations, where the statistical models used for viral load and measurement noise were obtained from [11]. In particular, in each simulation trial, a signal of length 961 was generated (independently from other trials) as follows: k coordinates were randomly chosen to take a nonzero value from the interval [1,1000] according to a (continuous) uniform distribution, and the remaining n − k coordinates were all set to value zero.…”

“…Table I summarizes our results for the proposed 2-STAP (both variants) and 2-STAMP schemes and the results for the Tapestry scheme for the same problem model (i.e., the same population size and the same viral load and noise distributions) where each measurement is made on a pool of 31 people (see [11]). In this table, m min , m max , m std , and m ave represent the minimum, maximum, standard deviation, and the average of the number of measurements used in 100 simulations, respectively.…”

“…For the same setting as the one in this work, a scheme called Tapestry was recently proposed in [11].…”

“…In [11], several different recovery algorithms from the CS literature were considered. In the following we explain one of these recovery algorithms which will also be used as part of the proposed schemes in this paper, and refer the reader to Appendix II for detailed description of the other recovery algorithms considered in [11].…”